Top 10 do’s and don’ts for maximising ROI of AI

Ima Miri
January 26, 2025

When it comes to implementing AI in business, many businesses overlook the foundational steps needed to ensure a successful AI strategy. It is important to not get caught up in the GenAI boom, focus on actionable steps to drive meaningful outcomes.

In this article, I put together 10 do's and don'ts to avoid when planning AI initiatives in your business. 

Do's 

1. Take a customer-centric approach 

Always prioritise the end-user experience when planning. Eventually, customer satisfaction will pay off in both financial and non-financial results. 

2. Research the tech 

Before implementing AI solutions, research the available technologies to find the best fit for your business needs. Understand the capabilities and limitations of Gen AI to set realistic expectations to avoid disappointment. 

3. Start small 

Begin with PoC and pilot projects to test the effectiveness of AI solutions. Small implementations allow you to measure impact and make adjustments before a full rollout. 

4. Monitor performance  

Regularly track the performance of your AI projects using key metrics aligned with your business goals. Use this data to refine models, adjust strategies, and make data-driven improvements over time. 

5. Build cross-functional teams 

Assemble teams that include members from various departments, such as IT, operations, finance, and marketing. Cross-functional collaboration ensures that AI initiatives are well-designed with considering different perspectives and expertise of various team members.  

6. Invest in employee training 

Equip your team with the necessary skills to work alongside AI projects. Training ensures smooth integration and helps employees leverage AI tools effectively. 

7. Data quality 

High-quality data is the backbone of effective AI solutions. Invest in data cleaning, integration, and management processes to ensure your AI projects have accurate and reliable data to work with. 

8. Prioritise data security and privacy 

Implement robust security measures to protect sensitive data. Ensure compliance with relevant regulations to maintain customer trust and avoid legal issues. 

9. Invest in scalable AI platforms 

Choose AI platforms and tools that are scalable and can grow with your business needs. Scalable solutions allow you to expand AI capabilities without significant additional investments. 

10. Invest in continuous learning 

Stay up to date with AI advancements and industry trends. 

 

While these do's lay the foundation for success, there are also some common pitfalls to avoid. 

Don’ts 

1. Ignore customer feedback 

Pay attention to how your customers interact with AI solutions. Use their feedback to refine and enhance the user experience. 

2. Underestimate complexity 

AI projects are not plug-and-play. At the same time, they add value and simplify processes for end users, they can bring complexity to the infrastructure and projects.

3. Rush into implementation 

Avoid impatiently integrating AI without a clear strategy. A rushed implementation can lead to wasted resources and insignificant results. 

4. Overlook human in the loop feedback 

While AI can automate many tasks, human supervision is still important. Maintain a balance between automation and human input to ensure quality and accountability. 

5. Ignore user adoption 

Ensure that the AI solutions are user-friendly and meet the needs of the end user. High user adoption rates lead to better data input, more accurate outputs, and higher ROI. 

6. Overlook ethical considerations 

Be mindful of the ethical implications of AI use. Ensure your AI projects are designed to prevent biases, respect privacy laws, and promote fairness and transparency. Adhere to ethical guidelines and legal regulations related to AI use.  

7. Ignore change management 

Prepare your team for AI adoption through training and change management programmes. Educated employees are more likely to embrace AI tools, leading to better utilisation and ROI.  

8. Underestimate costs 

Be realistic about the investment required for AI integration, including infrastructure, hardware and software, maintenance, and training costs. Plan your budget accordingly to avoid financial strain. 

9. Overlook the value of partnerships 

Collaborate with trusted technology providers, consultants, AI experts, and academic institutions. External expertise can accelerate implementation, provide valuable insights, and help avoid common pitfalls. 

10. Chase short-term goals and overlook long-term sustainability 

Develop a long-term AI strategy that considers future needs and technological advancements. Sustainable planning ensures that your AI investments continue to deliver value over time. 

AI is a transformative tool, and its success lies in strategic planning and thoughtful execution. 

At AI Point, we help businesses navigate the complexities of AI adoption, from strategy to implementation. Whether you're just starting or looking to scale, our expertise can make your journey seamless and impactful. Let’s connect and take the first step together toward building your AI-powered future.

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